Dual Selection Research Articles

Dual Heuristic Feature Selection Based on Genetic Algorithm and Binary Particle Swarm Optimization

The features selection is one of the data mining tools that used to select the most important features of a given dataset. It contributes to save time and memory during the handling a given dataset. According to these principles, we have proposed features selection method based on mixing two metaheuristic algorithms Binary Particle Swarm Optimization and Genetic Algorithm work individually. The K-Nearest Neighbour (K-NN) is used as an objective function to evaluate the proposed features selection algorithm. The Dual Heuristic Feature Selection based on Genetic Algorithm and Binary Particle Swarm Optimization (DHFS) test, and compared with 26 well-known datasets of UCI machine learning. The numeric experiments result imply that the DHFS better performance compared with full features and that selected by the mentioned algorithms (Genetic Algorithm and Binary Particle Swarm Optimization).

Comparative long-term effectiveness and safety of primary bariatric surgeries in treating type 2 diabetes mellitus in adults: a protocol for systematic review and network meta-analysis of randomised controlled trials

IntroductionBariatric surgeries are effective in treating obesity related comorbidities, including type 2 diabetes mellitus. More robust evidence is needed to facilitate choice of procedure. In this systemic review, we aim...

Defending against false data attacks in 3D grid-based MANET using soft computing approaches

Quality of service (QoS) is one of the major factors for current applications in mobile ad hoc networks (MANET). Due to the limited wireless link capabilities, a path with heavy load will lost battery within short period of time and maximizes the possibility of path disconnection and packet drops. Hence, optimal path is necessary to increase residual energy of the node. Dual CHs are selected by mobile node energy level, distance and expected relative mobility. The dual CH selection considers the residual energy of nodes, average distance to neighbors and number of neighbor nodes. Previously proposed multipath routing techniques reduce network traffic among multiple routes paths instead of sending packets via only one path. There are two research issues are still arisen in multipath routing that are packet redundancy and quality. We address these issues in the proposed optimal routing paradigm where the best path is selected instead of routing among all available paths. We propose hybrid routing scheme that combines type 2 fuzzy logic system to find available paths from source to the destination node and particle swarm optimization to identify a best path among the selected paths. Due to the lack of central monitoring system in MANET, security breach called false data injection attack may occur. To reveal this task, false data predicted on the source digital signature by upcoming cluster member. We implement our proposed approach in 3D grid-based MANET environment using NS3.26. We also compare our proposed approach performance with the conventional 2D routing schemes. Finally, the proposed approach shows higher QoS than others.

Dual feature selection and rebalancing strategy using metaheuristic optimization algorithms in X-ray image datasets

The imbalance and multi-dimension are two common problems in the medical image datasets, which affect the performances of the image processing procedures. The traditional methods to solve these two problems are notoriously difficult. Accordingly, this work employed metaheuristic methods to optimize the rebalancing process of the imbalanced class distribution for further use in the feature selection procedure for dimensionality reduction for the medical X-ray image datasets. Different metaheuristic algorithms were used to maximize the parameter values of the rebalancing and feature selection phases to preprocess the datasets. The proposed work devised a multi-objective optimization strategy in the process of the metaheuristic algorithms search to solve the problem of dual imbalanced dataset and feature selection. Afterward, a comparative study of the proposed optimized approach with the conventional methods was conducted to evaluate the proposed method performance. The results established the superiority of the proposed method to overcome the imbalanced and multi-dimensional problem. The proposed method generated a reasonable number of minority class samples and selected a sensible subset of features to ultimately obtain a very extraordinary accuracy with great credibility from a negative value of kappa and a false high accuracy. It produced higher credibility and correctness classification performance in the practical problem of medical X-ray images compared to other algorithms. Feature selection with Random-SMOTE (RSMOTE) using the self-adaptive Bat algorithm is superior to the optimization using particle swarm optimization. The proposed method using the Bat algorithm achieved 94.6% classification accuracy with 0.883 Kappa value using the lung X-ray first dataset.

Codebook-Free Compact Descriptor for Scalable Visual Search

The MPEG compact descriptors for visual search (CDVS) is a standard toward image matching and retrieval. To achieve high retrieval accuracy over a large scale image/video dataset, recent research efforts have demonstrated that employing extremely high-dimensional descriptors such as the Fisher vector (FV) and the vector of locally aggregated descriptors (VLAD) can yield good performance. Since the FV (or VLAD) possesses high discriminability but small visual vocabulary, it has been adopted by CDVS to construct a global compact descriptor. In this paper, we study the development of global compact descriptors in the completed CDVS standard and the emerging compact descriptors for video analysis (CDVA) standard, in which we formulate the FV (or VLAD) compression as a resource-constrained optimization problem. Accordingly, we propose a codebook-free aggregation method via dual selection to generate a global compact visual descriptor, which supports fast and accurate feature matching free of large visual codebooks, fulfilling the low memory requirement of mobile visual search at significantly reduced latency. Specifically, we investigate both sample-specific Gaussian component redundancy and bit dependency within a binary aggregated descriptor to produce compact binary codes. Our technique contributes to the scalable compressed Fisher vector (SCFV) adopted by the CDVS standard. Moreover, the SCFV descriptor is currently serving as the frame-level hand-crafted video feature, which inspires the inheritance of CDVS descriptors for the emerging CDVA standard. Furthermore, we investigate the positive complementary effect of our standard compliant compact descriptor and deep learning based features extracted from convolutional neural networks with significant mean average precision gains. Extensive evaluation over benchmark databases shows the significant merits of the codebook-free binary codes for scalable visual search.

Dual selection of Beauveria bassiana strains and complex substrate media for the massive production of submerged propagules with activity against the eucalyptus bronze bug Thaumastocoris peregrinus

ABSTRACTThe bronze bug Thaumastocoris peregrinus is an invasive pest, affecting Eucalyptus plantations worldwide. Although its natural enemy Cleruchoides noackae has been tested for the biological control of this pest, other strategies like the use of native entomopathogenic fungi are needed. For this, native virulent fungal isolates should be selected, massively multiplied in an efficient way, and prepared to obtain a stable product. Isolates of native Beauveria bassiana obtained from T. peregrinus and from different collections were screened for their virulence towards this insect and for their amenability to be massively produced in a low-input liquid submerged fermentation and prepared as a dry powder. Three out of six virulent strains were suitable for their massive production in a 2% corn flour suspension, achieving 109 submerged propagules/g of dehydrated preparation. The LC50 achieved by the dry submerged propagules did not differ from the LC50 of fresh aerial conidia. The proposed dual selection of strain and a complex substrate, and the procedures leading to the production of a dry preparation, allowed for high viability and virulence of the fungal spores of three strains.

CRISPR/Cas9-mediated one step bi-allelic change of genomic DNA in iPSCs and human RPE cells in vitro with dual antibiotic selection

CRISPR/Cas9 causes double-stranded DNA breaks that can undergo DNA repair either via non-homologous end joining (NHEJ) or, in the presence of a template, homology-directed repair (HDR). HDR is typically used to insert a specific genetic modification into the genome but has low efficiency compared to NHEJ, which is lowered even further when trying to create a homozygous change. In this study we devised a novel approach for homozygous single base editing based on utilising simultaneously two donor DNA templates cloned in plasmids with different antibiotic resistant genes. The donor templates were co-transfected alongside the CRISPR/Cas9 machinery into cells and a double antibiotic selection was optimised and allowed the isolation of viable desired clones. We applied the method for obtaining isogenic cells homozygous for variant B cystatin C, a recessive risk factor for age-related macular degeneration and Alzheimer’s disease, in both induced Pluripotent Stem Cells (iPSCs) and a human RPE cell line. Bi-allelic gene edited clones were validated by sequencing, demonstrating that the double antibiotic templates approach worked efficiently for both iPSCs and human differentiated cells. We propose that this one step gene editing approach can be used to improve the specificity and frequency of introducing homozygous modifications in mammalian cells.

English

Anthracnose (Colletotrichum lindemuthianum), Angular leaf spot (Pseudocercospora griseola) and Pythium root rot are important pathogens affecting common bean production in the tropics. A promising strategy to manage these diseases consists of combining several resistance (R) genes into one cultivar. The aim of the study was to determine genetic linkage between gene pairs, Co-42/Phg-2, on bean-chromosome Pv08 and Co-5/“P.ult” on-chromosome Pv07, to increase the efficiency of dual selection of resistance genes for major bean diseases, with molecular markers. The level of recombination was determined by tracking molecular markers for both BC3F6 and F2 generations. Recombination fraction r, among gene pairs, the likelihood of linkage, L(r), and logarithm of odds (LOD) scores were computed using the statistical relationship of likelihood which assumes a binomial distribution. The SCAR marker pair SAB3/PYAA19 for the gene pair Co-5/“P.ult” exhibited moderate linkage (r = 32 cM with a high LOD score of 9.2) for BC3F6 population, but relatively stronger linkage for the F2 population (r = 21 cM with a high LOD score of 18.7). However, the linkage among SCAR marker pair SH18/SN02, for the gene pair Co-42/Phg-2 was incomplete for BC3F6 population (r = 47 cM with a low LOD score of 0.16) as well as F2 population (r = 44 cM with a low LOD score of 0.7). Generally, the weak or incomplete genetic linkage between marker pairs studied showed that all the four genes mentioned earlier have to be tagged with a corresponding linked marker during selection. The approaches used in this study will contribute to two loci linkage mapping techniques in segregating plant populations.

模糊数学模型在职业双选因素评价中的应用

模糊数学模型在职业双选因素评价中的应用

A Dual Selection Marker Transformation System Using Agrobacterium tumefaciens for the Industrial Aspergillus oryzae 3.042.

Currently, the genetic modification of Aspergillus oryzae is mainly dependent on protoplastmediated transformation (PMT). In this study, we established a dual selection marker system in an industrial A. oryzae 3.042 strain by using Agrobacterium tumefaciens-mediated transformation (ATMT). We first constructed a uridine/uracil auxotrophic A. oryzae 3.042 strain and a pyrithiamine (PT)-resistance binary vector. Then, we established the ATMT system by using uridine/uracil auxotrophy and PT-resistance genes as selection markers. Finally, a dual selection marker ATMT system was developed. This study demonstrates a useful dual selection marker transformation system for genetic manipulations of A. oryzae 3.042.

Activity Landscape and Molecular Modeling to Explore the SAR of Dual Epigenetic Inhibitors: A Focus on G9a and DNMT1.

In this work we discuss the insights from activity landscape, docking and molecular dynamics towards the understanding of the structure-activity relationships of dual inhibitors of major epigenetic targets: lysine methyltransferase (G9a) and DNA methyltranferase 1 (DNMT1). The study was based on a novel data set of 50 published compounds with reported experimental activity for both targets. The activity landscape analysis revealed the presence of activity cliffs, e.g., pairs of compounds with high structure similarity but large activity differences. Activity cliffs were further rationalized at the molecular level by means of molecular docking and dynamics simulations that led to the identification of interactions with key residues involved in the dual activity or selectivity with the epigenetic targets.

Transaction costs and capability factors in dual or indirect distribution channel selection: An empirical analysis of Japanese manufacturers

This study focuses on manufacturers' selection of dual or indirect channels. Although several previous studies based on transaction cost theory investigate transaction cost factors in choosing dual or indirect channels mainly in the United States, this study examines transaction costs and capability factors for such a choice in Japan. The relationships are tested with survey data from Japanese industrial goods manufacturers (n = 429). Compared to previous studies, this study presents three important findings. First, unlike previous studies, two transaction cost factors—asset specificity and behavioral uncertainty—do not exhibit the relationships predicted by transaction cost theory. Interestingly, asset specificity is negatively related to the use of dual channels. Second, two capability factors not assessed in prior studies—market orientation capabilities and differences in channel members' capabilities—exhibit significant positive relationships with the selection of dual channels. Third, capability factors are found to be more important than transaction cost factors in explaining dual or indirect channels in Japan. This study also discusses the influence of the Japanese channel context on the results.

Weight reduction and cardiovascular benefits: Protocol for a systematic review and meta-analysis.

Background:There is widespread obesity paradox in cardiovascular diseases, the cardiovascular influence from weight management remains controversial. Moreover, previous publications indicating that different weight reduction extent might lead to various results. Thus, it is of importance to reassess the cardiovascular benefits of weight management strategies.Objectives:This review is designed to assess the association between weight loss and cardiovascular outcomes.Methods:Clinical trials including randomized control trials, observational studies reported a weight change before and after weight interventions including lifestyle intervention, as well as pharmacotherapies were included. Three major databases will be searched to retrieve the appropriate studies. Dual selection and abstraction of data will be conducted by 2 authors independently. The population, intervention, comparator, outcomes, study characteristics framework will be used to extract all the necessary data from included studies. The risk of bias assessment will be conducted in duplicate based on the Cochrane risk of bias guideline for randomized controlled trials (RCTs) and the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement for observational studies respectively. The primary outcomes will be the cardiovascular mortality, and the secondary outcomes are all-cause mortality and new cardiovascular events. A meta-analysis will be considered if there is sufficient homogeneity among selected studies. Follow the criteria of Grading of Recommendations, Assessment, Development and Evaluation (GRADE), the quality of the cumulative evidence will be evaluated.Results and conclusions:The results of this systematic review could provide reliable and concrete evidence for weight loss and its cardiovascular benefits.Prospero registration number: CRD42018108582.

A hybrid solution approach for fuzzy multiobjective dual supplier and material selection problem of carton box production systems

AbstractA novel optimization problem of carton box manufacturing industries is introduced in this paper. A mixed integer linear formulation with multiple objective functions is developed in order to determine the value of some criteria of carton raw sheets such as size, amount, and supplier under simultaneous minimization of multiple goals such as purchasing cost of raw sheets under discount policy, wastage remained from raw sheets, and quantity of surplus of carton boxes. In order to cope with the unstable market of this sector, some parameters of the proposed formulation such as demand value of the products and price given for raw sheets are assumed to be fuzzy numbers. To tackle such fuzzy multiobjective problem, first, the fuzzy problem is converted to a crisp form using the concepts of necessity‐based chance‐constrained modelling approach. Then a new hybrid form of the fuzzy programming approach is proposed to solve the obtained crisp multiobjective problem effectively. Computational experiments on a real case given by a carton box factory show the superior result of the proposed solution approach compared with the well‐known multiobjective solution methods taken from the literature.

Highly sensitive gas sensor based on Er-doped SnO2 nanostructures and its temperature dependent selectivity towards hydrogen and ethanol

In the present work, impact of Er3+ doping on the response and selectivity of SnO2 based gas sensor has been investigated in detail. X-ray diffraction (XRD) results confirmed formation of a tetragonal rutile structure of undoped and erbium doped SnO2 nanoparticles. It has been observed that specific surface area of nanoparticles has increased with increase in dopant concentration. The oxidation states and presence of erbium in SnO2 lattice has been confirmed by X-ray photoelectron spectroscopy (XPS). Photoluminescence (PL) analysis revealed that concentration of oxygen vacancies increases with increase in dopant incorporation. It has been observed that 3% Er-doped SnO2 sensor exhibited enhanced sensor response and temperature dependent selectivity towards ethanol and hydrogen at 240 and 360 ℃ respectively. The enhanced sensor response of the fabricated sensor has been ascribed to large surface area, enormous oxygen vacancies and elevated surface basicity of doped nanoparticles used. The tunable dual selectivity of 3% doped sensor towards ethanol and hydrogen makes it a perfect candidate for ethanol-hydrogen sensing for ethanol steam reforming systems combined to fuel cells.

Therapeutic effects of a mesenchymal stem cell‑based insulin‑like growth factor‑1/enhanced green fluorescent protein dual gene sorting system in a myocardial infarction rat model.

The present study was conducted in order to improve gene expression efficiency of insulin-like growth factor-1 (IGF-1)-transfected mesenchymal stem cells (MSCs) using a non-viral carrier and a simplified method of dual gene selection. The therapeutic efficacy of this MSC-based IGF-1/enhanced green fluorescent protein (EGFP) dual gene sorting system was evaluated in a rat myocardial infarction (MI) model. IGF-1 and EGFP genes were expressed in MSCs in vitro. The purity of dual gene-expressing MSCs was 95.1% by fluorescence-activated cell sorting. Transfected MSCs injected into rats were identified based on green fluorescence, with an increased signal intensity observed in rats injected with sorted cells, compared with unsorted cells. IGF-1 expression levels were additionally increased in the sorted group, and decreases in infarct size, fibrotic area and fraction of apoptotic cells were observed. These results demonstrated that IGF-1 overexpression protects against fibrosis and apoptosis in the myocardium and reduces infarct size following MI. Additionally, the present vector sorting system may potentially be applied to other types of stem cell-based gene therapy.

Viable Mice with Extensive Gene Humanization (25-kbp) Created Using Embryonic Stem Cell/Blastocyst and CRISPR/Zygote Injection Approaches

Here, we describe an expansion of the typical DNA size limitations associated with CRISPR knock-in technology, more specifically, the physical extent to which mouse genomic DNA can be replaced with donor (in this case, human) DNA at an orthologous locus by zygotic injection. Driving our efforts was the desire to create a whole animal model that would replace 17 kilobase pairs (kbp) of the mouse Bcl2l11 gene with the corresponding 25-kbp segment of human BCL2L11, including a conditionally removable segment (2.9-kbp) of intron 2, a cryptic human exon immediately 3′ of this, and a native human exon some 20 kbp downstream. Using two methods, we first carried out the replacement by employing a combination of bacterial artificial chromosome recombineering, classic embryonic stem cell (ESC) targeting, dual selection, and recombinase-driven cassette removal (ESC/Blastocyst Approach). Using a unique second method, we employed the same vector (devoid of its selectable marker cassettes), microinjecting it along with redundant single guide RNAs (sgRNAs) and Cas9 mRNA into mouse zygotes (CRISPR/Zygote Approach). In both instances, we were able to achieve humanization of Bcl2l11 to the extent designed, remove all selection cassettes, and demonstrate the functionality of the conditionally removable, loxP-flanked, 2.9-kbp intronic segment.

The Dual Threshold Limit of Financing and Formal Credit Availability with Chinese Rural Households: An Investigation Based on a Large Scale Survey

The literature on credit availability for rural households primarily focuses on the supply side, and largely ignores the demand side. This paper divided the credit process into three stages using large-scale household survey data. It also reviewed the credit process in other developing countries. A dual sample selection model was used to deal with the dual self-selection problem, which has been neglected in previous studies. This paper found that the main obstacle that farmers faced in obtaining financing was fear of applying for credit from formal financial institutions. In addition, there were significant differences in the determinants of different stages of the credit process of rural households.

Bimetal PdAu decorated SnO2 nanosheets based gas sensor with temperature-dependent dual selectivity for detecting formaldehyde and acetone

In this study, SnO2 nanosheets (NSs) was firstly prepared by the hydro-solvothermal treatment, and then decorated with Pd, Au and PdAu bimetallic nanoparticles (NPs) by an in situ reduction with ascorbic acid (AA). Their morphology, chemistry, and crystal structure were characterized at the nanoscale. It was found that SnO2 NSs were flower-like with thickness of 7–12 nm, and PdAu NPs with the size of 3–10 nm were dispersed uniformly on the surface of SnO2 NSs. Their gas sensing properties were carefully studied. The results demonstrated that the PdAu/SnO2 sensor can not only effectively detect acetone at 250 °C with response of 6.6 to 2 ppm acetone, but also detect formaldehyde at 110 °C with response of 4.1–2 ppm formaldehyde, and the corresponding detection limit is as low as 45 ppb and 30 ppb, respectively. Moreover, the PdAu/SnO2 sensor exhibited excellent reusability, and reliability to the low concentration of acetone and good anti-interference to humidity and other biomarkers in human breath. Compared with that decorated with their parent metal (Pd or Au), the enhanced response of SnO2 NSs decorated with PdAu bimetallic NPs may be ascribed to the chemical sensitization of Au, the electronic sensitization of Pd and the synergistic effect of PdAu bimetallic NPs. The PdAu/SnO2 sensor has a great potential application in detecting formaldehyde and diabetes diagnosis.

Engineering Riboswitches in Vivo Using Dual Genetic Selection and Fluorescence-Activated Cell Sorting.

Riboswitches, noncoding RNAs that bind a small molecule effector to control gene expression at the level of transcription or translation, are uniquely suited to meet challenges in synthetic biology. To expand the limited set of existing riboswitches, we developed a riboswitch discovery platform that couples dual genetic selection and fluorescence-activated cell sorting to identify novel riboswitches from a 108 random-sequence library in which the aptamer domain of the ThiM#2 riboswitch was replaced with an N40 sequence. In a proof-of-principle validation, we identified novel riboswitches for the small molecule theophylline. Our best riboswitch (Hit 3-5) displays 2.3-fold activation of downstream gene expression in the presence of theophylline. Random mutagenesis of Hit 3-5, coupled with selections and screens, afforded improved riboswitches displaying nearly 3-fold activation. To the best of our knowledge, this is the first report of in vivo directed evolution of an aptamer domain to generate a functional riboswitch.